





'''simple docstring'''

import numpy as np
from cva import COLOR_BGR2GRAY, CV_8UC3, cvtColor, filteraD, imread, imshow, waitKey







def    a__							(							lowercase   :	int,   lowercase   :	int,   lowercase   :	int,   lowercase   :	int,   lowercase   :	int,   lowercase   :	int )						->						np.ndarray:





     """simple docstring"""

     if (ksize % 2) == 0:
          _UpperCamelCase							       =			ksize + 1
     _UpperCamelCase							       =			np.zeros((ksize, ksize),   dtype=np.floataa )

     # each value
     for y in range(lowercase ):
          for x in range(lowercase ):
               # distance from center
               _UpperCamelCase							       =			x - ksize // 2
               _UpperCamelCase							       =			y - ksize // 2

               # degree to radiant
               _UpperCamelCase							       =			theta / 180 * np.pi
               _UpperCamelCase							       =			np.cos(_theta )
               _UpperCamelCase							       =			np.sin(_theta )

               # get kernel x
               _UpperCamelCase							       =			cos_theta * px + sin_theta * py

               # get kernel y
               _UpperCamelCase							       =			-sin_theta * px + cos_theta * py

               # fill kernel
               _UpperCamelCase							       =			np.exp(
                   -(_x**2 + gamma**2 * _y**2) / (2 * sigma**2) ) * np.cos(2 * np.pi * _x / lambd + psi )

     return gabor


if __name__ == "__main__":
   import doctest

   doctest.testmod()
   # read original image
   lowercase__		:     Any			=							imread('../image_data/lena.jpg')
   # turn image in gray scale value
   lowercase__		:     Optional[int]			=							cvtColor(img, COLOR_BGR2GRAY)

   # Apply multiple Kernel to detect edges
   lowercase__		:     Dict			=							np.zeros(gray.shape[:2])
   for theta in [0, 30, 60, 90, 1_20, 1_50]:
      lowercase__		:     str			=							gabor_filter_kernel(10, 8, theta, 10, 0, 0)
      out += filteraD(gray, CV_8UC3, kernel_aa)
   lowercase__		:     Dict			=							out / out.max() * 2_55
   lowercase__		:     List[str]			=							out.astype(np.uinta)

   imshow('Original', gray)
   imshow('Gabor filter with 20x20 mask and 6 directions', out)

   waitKey(0)











"""simple docstring"""





from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_sentencepiece_available,
    is_tokenizers_available,
    is_torch_available,
)


_SCREAMING_SNAKE_CASE   :							List[str]          =		{}

try:
  if not is_sentencepiece_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  _SCREAMING_SNAKE_CASE   :							str          =		['''NllbTokenizer''']

try:
  if not is_tokenizers_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  _SCREAMING_SNAKE_CASE   :							Optional[Any]          =		['''NllbTokenizerFast''']


if TYPE_CHECKING:
  try:
    if not is_sentencepiece_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .tokenization_nllb import NllbTokenizer

  try:
    if not is_tokenizers_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .tokenization_nllb_fast import NllbTokenizerFast

else:
  import sys

  _SCREAMING_SNAKE_CASE   :							Any          =		_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)




